Apply your GIS knowledge in this course on geospatial analysis, focusing on analysis tools, 3D data, working with rasters, projections, and environment variables. Through all four weeks of this course, we'll work through a project together - something unique to this course - from project conception, through data retrieval, initial data management and processing, and finally to our analysis products.
In this class you will learn the fundamentals of geospatial and environmental analysis during four week-long modules:
Week 1: Tour ArcToolbox and learn how to use common geospatial analysis tools built into ArcGIS
Week 2: Gain a working understanding of raster data models: symbolize, reproject, overlay, and assess rasters. Take a detour into 3D data models, and interpolation of observations into 3D surfaces and rasters
Week 3: Go in-depth on projections and coordinate systems, which are foundational to all GIS. Learn how to use environment variables to constrain your analyses and get better quality data products.
Week 4: Expand your knowledge of symbology. Learn how to visually display your data by classifying it in logical groupings and then symbolizing it on your map.
Take Geospatial and Environmental Analysis as a standalone course or as part of the Geographic Information Systems (GIS) Specialization. You should have equivalent experience to completing the first and second courses in this specialization, "Fundamentals of GIS" and "GIS Data Formats, Design, and Quality", before taking this course. By completing this third class in the Specialization you will gain the skills needed to succeed in the full program.

From the lesson

Working Through a Project

In the final module of this course, we're going to devote some time to discussing symbology. We've talked about symbology use a little bit in some of the other courses of the specialization, but this module provides a much more in-depth look at symbology use in ArcGIS. After viewing the videos in this module, you'll be able to design color ramps for your data, bin or classify your data appropriately, stretch raster boundaries, and copy and reuse symbology on multiple layers. Finally, we'll wrap up the geospatial analysis project before you begin work on the final (peer-reviewed) assignment for this course.